• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.6
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• pp.395-403
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• 2017

Image processing for object detection and identification has been studied for supply chain management application with various approaches. Among them, feature pointed detection algorithm is used to track an object or to recognize a position in automated supply chain systems and a depth image based feature point detection is recently highlighted in the application. The result of feature point detection is easily influenced by image noise. Also, the depth image has noise itself and it also affects to the accuracy of the detection results. In order to solve these problems, we propose a novel hybrid filtering mechanism for depth image based feature point detection, it shows better performance compared with conventional hybrid filtering mechanism.

• Journal of Aerospace System Engineering
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• v.10 no.1
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• pp.21-28
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• 2016

Orbit determination problems have been interest of many researchers for long time. Due to the high nonlinearity of the equation of motion and the measurement model, it is necessary to linearize the both equations. To avoid linearization, the filter based on Fokker-Planck equation is designed. with the extended Kalman filter update mechanism, in which the associated Fokker-Planck equation was solved efficiently and accurately via discrete quadrature and the measurement update was done through the extended Kalman filter update mechanism. This filter based on the DQMOM and the EKF update is applied to the orbit determination problem with appropriate modification to mitigate the filter smugness. Unlike the extended Kalman filter, the hybrid filter based on the DQMOM and the EKF update does not require the burdensome evaluation of the Jacobian matrix and Gaussian assumption for the system, and can still provide more accurate estimations of the state than those of the extended Kalman filter especially when measurements are sparse. Simulation results indicate that the advantages of the hybrid filter based on the DQMOM and the EKF update make it a promising alternative to the extended Kalman filter for orbit estimation problems.

• Journal of Power System Engineering
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• v.8 no.2
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• pp.31-38
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• 2004

The main purpose of this study is to investigate the characteristics of hybrid collection system combined with centrifugal force of cyclone and filtration of bag filter in one unit system. The experiment and numerical simulation are executed for the analysis of collection efficiency and pressure drop characteristics of hybrid system in comparison with those of a general fabric bag filter with the various experimental parameters such as inlet velocity(filtration velocity), dust concentration and dust type, etc.. In present system, dust particles tangentially coming into the system body are controlled by the centrifugal force effect, and the next collection is made out by the filtration mechanism in the fabric filter media. Therefore, the effective first collection causes the decrease of dust loading on the fabric filter, and it presents quite a lower pressure drop of fabric filter than that of a general fabric filter. At the inlet velocity, $21{\sim}27m/sec$ and inlet concentration(fly ash) $300mg/m^3$, pressure drops through the filter media of hybrid system are shown lower as $10{\sim}22mmH_2O$ comparing to those($17{\sim}33mmH_2O$) of a general fabric bag filter.

• Journal of Mechanical Science and Technology
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• v.16 no.3
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• pp.310-319
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• 2002

This paper deals with the analytical modeling, and the experimental verification of the strain rate self-sensing method using a hybrid adaptive filter for a cantilevered piezoelectric beam. The piezoelectric beam consists of two laminated lead zirconium titanates (PZT) on a metal shim. A mathematical model of the beam dynamics is derived by Hamilton's principle and the accuracy of the modeling is verified through the comparison with experimental results. For the strain rate estimation of the cantilevered piezoelectric beam, a self-sensing mechanism using a hybrid adaptive filter is considered. The discrete parts of this mechanism are realized by the DS1103 DSP board manufactured by dSPACE$\^$TM/. The efficacy of this method is investigated through the comparison of experimental results with the predictions from the derived analytical model.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1180-1188
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• 2008

As many systems depend on electronics, concern for fault tolerance is growing rapidly in the safety critical system such as intelligent vehicle. In order to make system fault tolerant, there has been a body of research mainly from aerospace field including predictive hybrid redundancy by Lee. Although the predictive hybrid redundancy has the fault tolerant mechanism to satisfy the fault tolerant requirement of safety crucial system such as x-by-wire system, it suffers form the variability of prediction performance according to the input feature of system. As an alternative to the prediction method of predictive hybrid redundancy for robust fault tolerant, Kalman prediction has attracted some attention because of its well-known and often-used with its structure called Kalman hybrid redundancy. In addition, several numerical simulation results are given where the Kalman hybrid redundancy outperforms with predictive smoothing voter.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.1
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• pp.147-154
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• 2012

The number of vehicles applied diesel engine are rapidly rising for fuel economy. Accompanying this trend, application of an after-treatment system is strictly required as a result of reinforced emission regulation. The Diesel Particulate Filter (DPF) system is considered as the most efficiency method to reduce particulate matter (PM) by car makers but also in retrofit market. In recently, various kinds of partial flow DPF are widely used for proper filtration performance and reducing of pressure drop but it is difficult to define the characteristics of these filters because the filtration mechanism is obscure according to the status of these systems. In this paper we investigated the characteristics of cell open type DPF according to the status of filter especially, PM loading. The PM loading mass in the p-DPF are predicted from increase of differential pressure of DPF and the trend of filtration efficiency so that we can measure filtration efficiency and Balance Point Temperature (BPT) of this p-DPF according to PM loading.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.103-111
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• 2004

The method of speaker normalization has been known as the successful method for improving the accuracy of speech recognition at speaker independent speech recognition system. A frequency warping approach is widely used method based on maximum likelihood for speaker normalization. This paper propose a new power spectrum warping approach to making improvement of speaker normalization better than a frequency warping. Th power spectrum warping uses Mel-frequency cepstrum analysis(MFCC) and is a simple mechanism to performing speaker normalization by modifying the power spectrum of Mel filter bank in MFCC. Also, this paper propose the hybrid VTN combined the Power spectrum warping and a frequency warping. Experiment of this paper did a comparative analysis about the recognition performance of the SKKU PBW DB applied each speaker normalization approach on baseline system. The experiment results have shown that a frequency warping is 2.06%, the power spectrum is 3.06%, and hybrid VTN is 4.07% word error rate reduction as of word recognition performance of baseline system.

• Asian Journal of Atmospheric Environment
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• v.12 no.1
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• pp.78-86
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• 2018

Filter-based sampling techniques are the conventional way to collect particulate matter, but particles collected and entangled in the filter fibers are difficult to be removed and thus not suited for the following cell- and animal-based exposure experiments. Collecting aerosol particles in powder form using a cyclone instead of a filter would be a possible way to solve this problem. We developed a hybrid virtual-impactor/cyclone high-volume fine and coarse particle sampler and assessed its performance. The developed system achieved 50% collection efficiency with components having the following aerodynamic cut-off diameters: virtual impactor, $2.4{\mu}m$; fine-particle cyclone, $0.18-0.30{\mu}m$; and coarse-particle cyclone, $0.7{\mu}m$. The virtual impactor used in our set-up had good $PM_{2.5}$ separation performance, comparable to that reported for a conventional real impactor. The newly developed sampler can collect fine and coarse particles simultaneously, in combination with exposure testing with collected fine- and coarse-particulate matter samples, should help researchers to elucidate the mechanism by which airborne particles result in adverse health effect in detail.